Module omnipy.modules.prefect.engine.prefect

Overview

View Source

import asyncio

from datetime import timedelta

from typing import Any, Callable, Type

from omnipy.api.protocols.public.compute import IsDagFlow, IsFuncFlow, IsLinearFlow, IsTask

from omnipy.api.protocols.public.config import IsPrefectEngineConfig

from omnipy.config.engine import PrefectEngineConfig

from omnipy.engine.job_runner import (DagFlowRunnerEngine,

                                      FuncFlowRunnerEngine,

                                      LinearFlowRunnerEngine,

                                      TaskRunnerEngine)

from omnipy.util.helpers import resolve

from .. import prefect_flow, prefect_task, PrefectFlow, PrefectTask, task_input_hash

class PrefectEngine(TaskRunnerEngine,

                    LinearFlowRunnerEngine,

                    DagFlowRunnerEngine,

                    FuncFlowRunnerEngine):

    """Job runner engine for Prefect"""

    def _init_engine(self) -> None:

        ...

    def _update_from_config(self) -> None:

        ...

    @classmethod

    def get_config_cls(cls) -> Type[IsPrefectEngineConfig]:

        return PrefectEngineConfig

    # TaskRunnerEngine

    def _init_task(self, task: IsTask, call_func: Callable) -> PrefectTask:

        assert isinstance(self._config, PrefectEngineConfig)

        task_kwargs = dict(

            name=task.name,

            cache_key_fn=task_input_hash if self._config.use_cached_results else None,

            cache_expiration=timedelta(days=1))

        if task.has_coroutine_func():

            @prefect_task(**task_kwargs)

            async def run_task(*inner_args, **inner_kwargs):

                return await call_func(*inner_args, **inner_kwargs)

        else:

            @prefect_task(**task_kwargs)

            def run_task(*inner_args, **inner_kwargs):

                return call_func(*inner_args, **inner_kwargs)

        return run_task

    def _run_task(self, state: PrefectTask, task: IsTask, call_func: Callable, *args,

                  **kwargs) -> Any:

        _prefect_task = state

        if task.in_flow_context:

            return _prefect_task(*args, **kwargs)

        else:

            flow_kwargs = dict(name=task.name)

            if asyncio.iscoroutinefunction(_prefect_task):

                @prefect_flow(**flow_kwargs)

                async def task_flow(*inner_args, **inner_kwargs):

                    return await resolve(_prefect_task(*inner_args, **inner_kwargs))

            else:

                @prefect_flow(**flow_kwargs)

                def task_flow(*inner_args, **inner_kwargs):

                    return _prefect_task(*inner_args, **inner_kwargs)

            return task_flow(*args, **kwargs)

    # LinearFlowRunnerEngine

    def _init_linear_flow(self, linear_flow: IsLinearFlow) -> Any:

        assert isinstance(self._config, PrefectEngineConfig)

        flow_kwargs = dict(name=linear_flow.name,)

        call_func = self.default_linear_flow_run_decorator(linear_flow)

        if linear_flow.has_coroutine_func():

            @prefect_flow(**flow_kwargs)

            async def run_linear_flow(*inner_args, **inner_kwargs):

                with linear_flow.flow_context:

                    return await resolve(call_func(*inner_args, **inner_kwargs))

        else:

            @prefect_flow(**flow_kwargs)

            def run_linear_flow(*inner_args, **inner_kwargs):

                with linear_flow.flow_context:

                    return call_func(*inner_args, **inner_kwargs)

        return run_linear_flow

    def _run_linear_flow(self, state: Any, linear_flow: IsLinearFlow, *args, **kwargs) -> Any:

        _prefect_flow = state

        return _prefect_flow(*args, **kwargs)

    # DagFlowRunnerEngine

    def _init_dag_flow(self, dag_flow: IsDagFlow) -> Any:

        assert isinstance(self._config, PrefectEngineConfig)

        flow_kwargs = dict(name=dag_flow.name,)

        call_func = self.default_dag_flow_run_decorator(dag_flow)

        if dag_flow.has_coroutine_func():

            @prefect_flow(**flow_kwargs)

            async def run_dag_flow(*inner_args, **inner_kwargs):

                with dag_flow.flow_context:

                    return await resolve(call_func(*inner_args, **inner_kwargs))

        else:

            @prefect_flow(**flow_kwargs)

            def run_dag_flow(*inner_args, **inner_kwargs):

                with dag_flow.flow_context:

                    return call_func(*inner_args, **inner_kwargs)

        return run_dag_flow

    def _run_dag_flow(self, state: PrefectFlow, flow: IsDagFlow, *args, **kwargs) -> Any:

        _prefect_flow = state

        return _prefect_flow(*args, **kwargs)

    # FuncFlowRunnerEngine

    def _init_func_flow(self, func_flow: IsFuncFlow, call_func: Callable) -> object:

        assert isinstance(self._config, PrefectEngineConfig)

        flow_kwargs = dict(name=func_flow.name,)

        if func_flow.has_coroutine_func():

            @prefect_flow(**flow_kwargs)

            async def run_func_flow(*inner_args, **inner_kwargs):

                with func_flow.flow_context:

                    return await resolve(call_func(*inner_args, **inner_kwargs))

        else:

            @prefect_flow(**flow_kwargs)

            def run_func_flow(*inner_args, **inner_kwargs):

                with func_flow.flow_context:

                    return call_func(*inner_args, **inner_kwargs)

        return run_func_flow

    def _run_func_flow(self,

                       state: Any,

                       func_flow: IsFuncFlow,

                       call_func: Callable,

                       *args,

                       **kwargs) -> Any:

        _prefect_flow = state

        return _prefect_flow(*args, **kwargs)

# TODO: Refactor redundant code

Classes

PrefectEngine

class PrefectEngine(

)

Job runner engine for Prefect

View Source

class PrefectEngine(TaskRunnerEngine,

                    LinearFlowRunnerEngine,

                    DagFlowRunnerEngine,

                    FuncFlowRunnerEngine):

    """Job runner engine for Prefect"""

    def _init_engine(self) -> None:

        ...

    def _update_from_config(self) -> None:

        ...

    @classmethod

    def get_config_cls(cls) -> Type[IsPrefectEngineConfig]:

        return PrefectEngineConfig

    # TaskRunnerEngine

    def _init_task(self, task: IsTask, call_func: Callable) -> PrefectTask:

        assert isinstance(self._config, PrefectEngineConfig)

        task_kwargs = dict(

            name=task.name,

            cache_key_fn=task_input_hash if self._config.use_cached_results else None,

            cache_expiration=timedelta(days=1))

        if task.has_coroutine_func():

            @prefect_task(**task_kwargs)

            async def run_task(*inner_args, **inner_kwargs):

                return await call_func(*inner_args, **inner_kwargs)

        else:

            @prefect_task(**task_kwargs)

            def run_task(*inner_args, **inner_kwargs):

                return call_func(*inner_args, **inner_kwargs)

        return run_task

    def _run_task(self, state: PrefectTask, task: IsTask, call_func: Callable, *args,

                  **kwargs) -> Any:

        _prefect_task = state

        if task.in_flow_context:

            return _prefect_task(*args, **kwargs)

        else:

            flow_kwargs = dict(name=task.name)

            if asyncio.iscoroutinefunction(_prefect_task):

                @prefect_flow(**flow_kwargs)

                async def task_flow(*inner_args, **inner_kwargs):

                    return await resolve(_prefect_task(*inner_args, **inner_kwargs))

            else:

                @prefect_flow(**flow_kwargs)

                def task_flow(*inner_args, **inner_kwargs):

                    return _prefect_task(*inner_args, **inner_kwargs)

            return task_flow(*args, **kwargs)

    # LinearFlowRunnerEngine

    def _init_linear_flow(self, linear_flow: IsLinearFlow) -> Any:

        assert isinstance(self._config, PrefectEngineConfig)

        flow_kwargs = dict(name=linear_flow.name,)

        call_func = self.default_linear_flow_run_decorator(linear_flow)

        if linear_flow.has_coroutine_func():

            @prefect_flow(**flow_kwargs)

            async def run_linear_flow(*inner_args, **inner_kwargs):

                with linear_flow.flow_context:

                    return await resolve(call_func(*inner_args, **inner_kwargs))

        else:

            @prefect_flow(**flow_kwargs)

            def run_linear_flow(*inner_args, **inner_kwargs):

                with linear_flow.flow_context:

                    return call_func(*inner_args, **inner_kwargs)

        return run_linear_flow

    def _run_linear_flow(self, state: Any, linear_flow: IsLinearFlow, *args, **kwargs) -> Any:

        _prefect_flow = state

        return _prefect_flow(*args, **kwargs)

    # DagFlowRunnerEngine

    def _init_dag_flow(self, dag_flow: IsDagFlow) -> Any:

        assert isinstance(self._config, PrefectEngineConfig)

        flow_kwargs = dict(name=dag_flow.name,)

        call_func = self.default_dag_flow_run_decorator(dag_flow)

        if dag_flow.has_coroutine_func():

            @prefect_flow(**flow_kwargs)

            async def run_dag_flow(*inner_args, **inner_kwargs):

                with dag_flow.flow_context:

                    return await resolve(call_func(*inner_args, **inner_kwargs))

        else:

            @prefect_flow(**flow_kwargs)

            def run_dag_flow(*inner_args, **inner_kwargs):

                with dag_flow.flow_context:

                    return call_func(*inner_args, **inner_kwargs)

        return run_dag_flow

    def _run_dag_flow(self, state: PrefectFlow, flow: IsDagFlow, *args, **kwargs) -> Any:

        _prefect_flow = state

        return _prefect_flow(*args, **kwargs)

    # FuncFlowRunnerEngine

    def _init_func_flow(self, func_flow: IsFuncFlow, call_func: Callable) -> object:

        assert isinstance(self._config, PrefectEngineConfig)

        flow_kwargs = dict(name=func_flow.name,)

        if func_flow.has_coroutine_func():

            @prefect_flow(**flow_kwargs)

            async def run_func_flow(*inner_args, **inner_kwargs):

                with func_flow.flow_context:

                    return await resolve(call_func(*inner_args, **inner_kwargs))

        else:

            @prefect_flow(**flow_kwargs)

            def run_func_flow(*inner_args, **inner_kwargs):

                with func_flow.flow_context:

                    return call_func(*inner_args, **inner_kwargs)

        return run_func_flow

    def _run_func_flow(self,

                       state: Any,

                       func_flow: IsFuncFlow,

                       call_func: Callable,

                       *args,

                       **kwargs) -> Any:

        _prefect_flow = state

        return _prefect_flow(*args, **kwargs)

---

Static methods

default_dag_flow_run_decorator

def default_dag_flow_run_decorator(
    dag_flow: omnipy.api.protocols.public.compute.IsDagFlow
) -> Any

Parameters:

Name	Type	Description	Default
dag_flow	IsDagFlow

Returns:

Type	Description
Any

View Source

    @staticmethod

    def default_dag_flow_run_decorator(dag_flow: IsDagFlow) -> Any:  # noqa: C901

        def _inner_run_dag_flow(*args: object, **kwargs: object):

            results = {}

            result = None

            with dag_flow.flow_context:

                for i, job in enumerate(dag_flow.task_templates):

                    if i == 0:

                        results = dag_flow.get_call_args(*args, **kwargs)

                    param_keys = set(inspect.signature(job).parameters.keys())

                    # TODO: Refactor to remove dependency

                    #       Also, add test for not allowing override of fixed_params

                    if hasattr(job, 'param_key_map'):

                        for key, val in job.param_key_map.items():

                            if key in param_keys:

                                param_keys.remove(key)

                                param_keys.add(val)

                    if hasattr(job, 'fixed_params'):

                        for key in job.fixed_params.keys():

                            if key in param_keys:

                                param_keys.remove(key)

                    params = {key: val for key, val in results.items() if key in param_keys}

                    result = job(**params)

                    if isinstance(result, dict) and len(result) > 0:

                        results.update(result)

                    else:

                        results[job.name] = result

            return result

        return _inner_run_dag_flow

default_linear_flow_run_decorator

def default_linear_flow_run_decorator(
    linear_flow: omnipy.api.protocols.public.compute.IsLinearFlow
) -> Any

Parameters:

Name	Type	Description	Default
linear_flow	IsLinearFlow

Returns:

Type	Description
Any

View Source

    @staticmethod

    def default_linear_flow_run_decorator(linear_flow: IsLinearFlow) -> Any:

        def _inner_run_linear_flow(*args: object, **kwargs: object):

            result = None

            with linear_flow.flow_context:

                for i, job in enumerate(linear_flow.task_templates):

                    # TODO: Better handling of kwargs

                    if i == 0:

                        result = job(*args, **kwargs)

                    else:

                        result = job(*args)

                    args = (result,)

            return result

        return _inner_run_linear_flow

get_config_cls

def get_config_cls(

) -> Type[omnipy.api.protocols.public.config.IsPrefectEngineConfig]

Specification of config class mapped to an Engine subclass. Must be implemented by all

subclasses of Engine. If no configuration is needed, then the EngineConfig class should be returned.

Returns:

Type	Description
Type[IsPrefectEngineConfig]	Class implementing the IsEngineConfig protocol

View Source

    @classmethod

    def get_config_cls(cls) -> Type[IsPrefectEngineConfig]:

        return PrefectEngineConfig

Methods

apply_dag_flow_decorator

def apply_dag_flow_decorator(
    self,
    dag_flow: omnipy.api.protocols.public.compute.IsDagFlow,
    job_callback_accept_decorator: Callable
) -> None

Parameters:

Name	Type	Description	Default
dag_flow	IsDagFlow
job_callback_accept_decorator	Callable

Returns:

Type	Description
NoneType

View Source

    def apply_dag_flow_decorator(self, dag_flow: IsDagFlow,

                                 job_callback_accept_decorator: Callable) -> None:

        def _dag_flow_decorator(call_func: Callable) -> Callable:

            self._register_job_state(dag_flow, RunState.INITIALIZED)

            state = self._init_dag_flow(dag_flow)

            def _dag_flow_runner_call_func(*args: object, **kwargs: object) -> Any:

                self._register_job_state(dag_flow, RunState.RUNNING)

                flow_result = self._run_dag_flow(state, dag_flow, *args, **kwargs)

                return self._decorate_result_with_job_finalization_detector(dag_flow, flow_result)

            return _dag_flow_runner_call_func

        job_callback_accept_decorator(_dag_flow_decorator)

apply_func_flow_decorator

def apply_func_flow_decorator(
    self,
    func_flow: omnipy.api.protocols.public.compute.IsFuncFlow,
    job_callback_accept_decorator: Callable
) -> None

Parameters:

Name	Type	Description	Default
func_flow	IsFuncFlow
job_callback_accept_decorator	Callable

Returns:

Type	Description
NoneType

View Source

    def apply_func_flow_decorator(self,

                                  func_flow: IsFuncFlow,

                                  job_callback_accept_decorator: Callable) -> None:

        def _func_flow_decorator(call_func: Callable) -> Callable:

            self._register_job_state(func_flow, RunState.INITIALIZED)

            state = self._init_func_flow(func_flow, call_func)

            def _func_flow_runner_call_func(*args: object, **kwargs: object) -> Any:

                self._register_job_state(func_flow, RunState.RUNNING)

                with func_flow.flow_context:

                    flow_result = self._run_func_flow(state, func_flow, call_func, *args, **kwargs)

                    return self._decorate_result_with_job_finalization_detector(

                        func_flow, flow_result)

            return _func_flow_runner_call_func

        job_callback_accept_decorator(_func_flow_decorator)

apply_linear_flow_decorator

def apply_linear_flow_decorator(
    self,
    linear_flow: omnipy.api.protocols.public.compute.IsLinearFlow,
    job_callback_accept_decorator: Callable
) -> None

Parameters:

Name	Type	Description	Default
linear_flow	IsLinearFlow
job_callback_accept_decorator	Callable

Returns:

Type	Description
NoneType

View Source

    def apply_linear_flow_decorator(self,

                                    linear_flow: IsLinearFlow,

                                    job_callback_accept_decorator: Callable) -> None:

        def _linear_flow_decorator(call_func: Callable) -> Callable:

            self._register_job_state(linear_flow, RunState.INITIALIZED)

            state = self._init_linear_flow(linear_flow)

            def _linear_flow_runner_call_func(*args: object, **kwargs: object) -> Any:

                self._register_job_state(linear_flow, RunState.RUNNING)

                flow_result = self._run_linear_flow(state, linear_flow, *args, **kwargs)

                return self._decorate_result_with_job_finalization_detector(

                    linear_flow, flow_result)

            return _linear_flow_runner_call_func

        job_callback_accept_decorator(_linear_flow_decorator)

apply_task_decorator

def apply_task_decorator(
    self,
    task: omnipy.api.protocols.public.compute.IsTask,
    job_callback_accept_decorator: Callable
) -> None

Parameters:

Name	Type	Description	Default
task	IsTask
job_callback_accept_decorator	Callable

Returns:

Type	Description
NoneType

View Source

    def apply_task_decorator(self, task: IsTask, job_callback_accept_decorator: Callable) -> None:

        def _task_decorator(call_func: Callable) -> Callable:

            self._register_job_state(task, RunState.INITIALIZED)

            state = self._init_task(task, call_func)

            def _task_runner_call_func(*args: object, **kwargs: object) -> Any:

                self._register_job_state(task, RunState.RUNNING)

                task_result = self._run_task(state, task, call_func, *args, **kwargs)

                return self._decorate_result_with_job_finalization_detector(task, task_result)

            return _task_runner_call_func

        job_callback_accept_decorator(_task_decorator)

set_config

def set_config(
    self,
    config: omnipy.api.protocols.public.config.IsEngineConfig
) -> None

Parameters:

Name	Type	Description	Default
config	IsEngineConfig

Returns:

Type	Description
NoneType

View Source

    def set_config(self, config: IsEngineConfig) -> None:

        self._config = config

        self._update_from_config()

set_registry

def set_registry(
    self,
    registry: omnipy.api.protocols.private.log.IsRunStateRegistry | None
) -> None

Parameters:

Name	Type	Description	Default
registry	omnipy.api.protocols.private.log.IsRunStateRegistry	None

Returns:

Type	Description
NoneType

View Source

    def set_registry(self, registry: IsRunStateRegistry | None) -> None:

        self._registry = registry